Tablesaw is a dataframe and visualization library, as well as utilities for loading, transforming, filtering, and summarizing data. It's fast and careful with memory. If you work with data in Java, it may save you time and effort. Tablesaw also supports descriptive statistics and integrates well with the Smile machine learning library.
Data processing & transformation
- Import data from RDBMS, Excel, CSV, JSON, HTML, or Fixed Width text files, whether they are local or remote (http, S3, etc.)
- Export data to CSV, JSON, HTML or Fixed Width files.
- Combine tables by appending or joining
- Add and remove columns or rows
- Sort, Group, Query
- Map/Reduce operations
- Handle missing values
- Descriptive stats: mean, min, max, median, sum, product, standard deviation, variance, percentiles, geometric mean, skewness, kurtosis, etc.
Add tablesaw-core to your project. You can find the version number for the latest release in the release notes:
<dependency> <groupId>tech.tablesaw</groupId> <artifactId>tablesaw-core</artifactId> <version>VERSION_NUMBER_GOES_HERE</version> </dependency>
You may also add supporting projects:
tablesaw-beakerx- for using Tablesaw inside BeakerX
tablesaw-excel- for using Excel workbooks
tablesaw-html- for using HTML
tablesaw-json- for using JSON
tablesaw-jsplot- for creating charts
External supporting projects - outside of this organization:
Documentation and support
- Start here: https://jtablesaw.github.io/tablesaw/gettingstarted
- Then see our documentation page: https://jtablesaw.github.io/tablesaw/ and the Tablesaw User Guide.
- Ask questions, make suggestions, or tell us how you're using Tablesaw in the new GitHub discussions forum.
- Feature requests and bug reports can be made on the issues tab.
Eclipse uses may find etablesaw useful. It provides Eclipse integration aimed at turning Eclipse into a data workbench.